Using Harvest Slot Limits to Promote Stock Recovery and Broaden Age Structure in Marine Recreational Fisheries: A Case Study
Bibliographic record
Abstract
Abstract Fish populations with broad age distributions are expected to have higher reproductive capacity than age-truncated populations because of the disproportionate contributions of older fish. Harvest slot limits, an expected means of ameliorating age truncation, are modeled for Tautog Tautoga onitis in an overfished population subunit that is experiencing overfishing. Tautog, currently managed with a 40-cm minimum size limit (MSL), is a candidate species for slots because it is relatively long-lived and slow-growing, with low discard mortality. We evaluated changes in biomass and abundance at age relative to management with the current MSL regulations using a forward population simulation model for four slots: 35–45 cm (small–wide), 38–42 cm (small–narrow), 40–50 cm (large–wide), and 43–47 cm (large-narrow), inclusive of lower and upper length limits. Angler behavioral responses were evaluated at 0, 10, and 20% noncompliance with the upper slot limit. The biomass and number of fish removed were reduced with harvest slot limit management relative to the MSL, but because the harvest was redirected to smaller fish the reduction in numbers removed was not as large as the reduction in biomass removed. Slot limits broadened the age structure within 10 years by reducing fishing mortality on extant fish. Median spawning stock biomass (SSB) recovered more quickly in three of the slots than with MSL regulation (3–6 years to reach SSB associated with a fishing mortality that yields 30% spawners per recruit as compared to 9 years with MSL management). We concluded that harvest slot limits can broaden age structure and restore biomass in overfished fisheries, but they should be evaluated when managing coastal fisheries as a reduction in biomass removed is required.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".